Publications

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Journal Article
A. Presenti, Sijbers, J., and De Beenhouwer, J., Dynamic few-view X-ray imaging for inspection of CAD-based objects, Expert Systems with Applications, vol. 180, p. 115012, 2021.
A. Dabravolski, Batenburg, K. J., and Sijbers, J., Dynamic Angle Selection in X-ray Computed Tomography, Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, vol. 324, pp. 17-24, 2014.
K. J. Batenburg, Palenstijn, W. J., Balazs, P., and Sijbers, J., Dynamic angle selection in binary tomography, Computer Vision and Image Understanding, vol. 117, no. 5, pp. 306–318, 2013.PDF icon Download paper (2.71 MB)
T. De Bondt, Van Hecke, W., Veraart, J., Leemans, A., Sijbers, J., Sunaert, S., Jacquemyn, Y., and Parizel, P. M., Does the use of hormonal contraceptives cause microstructural changes in cerebral white matter? Preliminary results of a DTI and tractography study., European radiology, vol. 23, no. 1, pp. 57-64, 2013.PDF icon Download paper (411.18 KB)
W. J. Palenstijn, Bédorf, J., Sijbers, J., and Batenburg, K. J., A distributed ASTRA Toolbox, Advanced Structural and Chemical Imaging, vol. 2, no. 19, 2016.PDF icon Download paper (2.7 MB)
A. Smolders, Martino, D. F., Staeren, N., Scheunders, P., Sijbers, J., Goebel, R., and Formisano, E., Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis, Magnetic Resonance Imaging, vol. 25, pp. 860-868, 2007.PDF icon Download paper (658.36 KB)
H. Segers, Palenstijn, W. J., Batenburg, K. J., and Sijbers, J., Discrete Tomography in MRI: a Simulation Study, Fundamenta Informaticae, vol. 125, no. 3-4, pp. 223-237, 2013.
E. Van de Casteele, Perilli, E., Van Aarle, W., Reynolds, K., and Sijbers, J., Discrete tomography in an in vivo small animal bone study, Journal of Bone and Mineral Metabolism, vol. 36, no. 1, pp. 40–53, 2018.
J. Christopher, Lumbeeck, L. - P., Paramonov, P., De Beenhouwer, J., and Sijbers, J., Discrete Terahertz tomography: a simulation study, e-Journal of Nondestructive Testing, vol. 27, no. 3, 2022.PDF icon Download paper (345.5 KB)
P. Van Dyck, Billiet, T., Desbuquoit, D., Verdonk, P., Heusdens, C. H., Roelant, E., Sijbers, J., and Froeling, M., Diffusion tensor imaging of the anterior cruciate ligament graft following reconstruction: a longitudinal study, European Radiology, vol. 34, pp. 6673–6684, 2020.
P. Van Dyck, Froeling, M., De Smet, E., Pullens, P., Torfs, M., Verdonck, P., Sijbers, J., Parizel, P. M., and Jeurissen, B., Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft, Journal of Magnetic Resonance Imaging, vol. 46, no. 5, pp. 1423–1432, 2017.
P. Van Dyck, Froeling, M., Heusdens, C. H. W., Sijbers, J., Ribbens, A., and Billiet, T., Diffusion Tensor Imaging of the Anterior Cruciate Ligament Following Primary Repair with Internal Bracing: a Longitudinal Study, Journal of Orthopaedic Research , vol. 39, pp. 1318–1330, 2021.
N. Van Camp, Blockx, I., Verhoye, M., Casteels, C., Coun, F., Leemans, A., Sijbers, J., Baekelandt, V., Van Laere, K., and Van Der Linden, A., Diffusion tensor imaging in a rat model of Parkinson's disease after lesioning of the nigrostriatal tract., NMR in biomedicine, vol. 22, no. 7, pp. 697-706, 2009.
W. Van Hecke, Nagels, G., Emonds, G., Leemans, A., Sijbers, J., van Goethem, J., and Parizel, P. M., A diffusion tensor imaging group study of the spinal cord in multiple sclerosis patients with and without T2 spinal cord lesions., Journal of magnetic resonance imaging : JMRI, vol. 30, no. 1, pp. 25-34, 2009.PDF icon Download paper (902.67 KB)
Z. Mai, Verhoye, M., Van Der Linden, A., and Sijbers, J., Diffusion tensor image up-sampling: a registration-based approach, Magnetic resonance Imaging, vol. 28, pp. 1497-1506, 2010.PDF icon Download paper (814.96 KB)
Q. Collier, Veraart, J., Jeurissen, B., Vanhevel, F., Pullens, P., Parizel, P. M., den Dekker, A. J., and Sijbers, J., Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach, Magnetic Resonance in Medicine, vol. 80, no. 2, pp. 802-813, 2018.PDF icon Download paper (1.93 MB)
G. Vanhoutte, Pereson, S., Delgado Y Palacios, R., Guns, P. - J., Asselbergh, B., Veraart, J., Sijbers, J., Verhoye, M., Van Broeckhoven, C., and Van Der Linden, A., Diffusion kurtosis imaging to detect amyloidosis in an APP/PS1 mouse model for Alzheimer's disease, Magnetic Resonance in Medicine, vol. 69, no. 4, pp. 1115–1121, 2013.
C. Guglielmetti, Veraart, J., Roelant, E., Mai, Z., Daans, J., Van Audekerke, J., Naeyaert, M., Vanhoutte, G., Delgado Y Palacios, R., Praet, J., Fieremans, E., Ponsaerts, P., Sijbers, J., Van Der Linden, A., and Verhoye, M., Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination, NeuroImage, vol. 125, pp. 363–377, 2016.
S. Van Cauter, Veraart, J., Sijbers, J., Peeters, R. R., Himmelreich, U., Gool, V. S., Van Calenbergh, F., De Vleeschouwer, S., Van Hecke, W., and Sunaert, S., Diffusion kurtosis imaging in the grading of gliomas, Radiology, vol. 2, pp. 492-501, 2012.
J. Praet, Manyakov, N., Muchene, L., Mai, Z., Terzopoulos, V., De Backer, S., Torremans, A., Guns, P. - J., Van De Casteele, T., Bottelbergs, A., Van Broeck, B., Sijbers, J., Smeets, D., Shkedy, Z., Bijnens, L., Pemberton, D., Schmidt, M., Van Der Linden, A., and Verhoye, M., Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid β-induced pathology., Alzheimer's Research & Therapy , vol. 10, no. 1, pp. 1-16, 2018.
H. Struyfs, Van Hecke, W., Veraart, J., Sijbers, J., Slaets, S., De Belder, M., Wuyts, L., Peters, B., Sleegers, K., Robberecht, C., Van Broeckhoven, C., De Belder, F., Parizel, P. M., and Engelborghs, S., Diffusion Kurtosis Imaging: a possible MRI biomarker for AD diagnosis?, Journal of Alzheimer’s Disease, vol. 48, pp. 937-948, 2015.PDF icon Download paper (374.95 KB)
J. Gonnissen, De Backer, A., den Dekker, A. J., Sijbers, J., and Van Aert, S., Detecting and locating light atoms from high-resolution STEM images: the quest for a single optimal design Ultramicroscopy, Ultramicroscopy, vol. 170, pp. 128-138, 2016.
J. Veraart, Novikov, D. S., Daan, C., Ades-Aron, B., Sijbers, J., and Fieremans, E., Denoising of diffusion MRI using random matrix theory, NeuroImage, vol. 142, pp. 384-396, 2016.PDF icon Download paper (4.53 MB)
M. Yosifov, Weinberger, P., Reiter, M., Fröhler, B., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations, e-Journal of Nondestructive Testing, vol. 28, no. 3, 2023.PDF icon Download paper (2.37 MB)
C. Smekens, Beirinckx, Q., Bosmans, F., Vanhevel, F., Snoeckx, A., Sijbers, J., Jeurissen, B., Janssens, T., and Van Dyck, P., Deep Learning-Enhanced Accelerated 2D TSE and 3D Super-Resolution Dixon TSE for Rapid Comprehensive Knee Joint Assessment, Investigative Radiology, In Press.

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